View source on GitHub
|
Initializer that generates tensors with constant values.
Inherits From: Initializer
tf.keras.initializers.Constant(
value=0
)
Also available via the shortcut function tf.keras.initializers.constant.
Only scalar values are allowed. The constant value provided must be convertible to the dtype requested when calling the initializer.
Examples:
# Standalone usage:initializer = tf.keras.initializers.Constant(3.)values = initializer(shape=(2, 2))
# Usage in a Keras layer:initializer = tf.keras.initializers.Constant(3.)layer = tf.keras.layers.Dense(3, kernel_initializer=initializer)
Args | |
|---|---|
value
|
A Python scalar. |
Methods
from_config
@classmethodfrom_config( config )
Instantiates an initializer from a configuration dictionary.
Example:
initializer = RandomUniform(-1, 1)
config = initializer.get_config()
initializer = RandomUniform.from_config(config)
| Args | |
|---|---|
config
|
A Python dictionary, the output of get_config.
|
| Returns | |
|---|---|
A tf.keras.initializers.Initializer instance.
|
get_config
get_config()
Returns the configuration of the initializer as a JSON-serializable dict.
| Returns | |
|---|---|
| A JSON-serializable Python dict. |
__call__
__call__(
shape, dtype=None
)
Returns a tensor object initialized to self.value.
| Args | |
|---|---|
shape
|
Shape of the tensor. |
dtype
|
Optional dtype of the tensor. If not specified,
tf.keras.backend.floatx() is used,
which default to float32 unless you configured it otherwise
(via tf.keras.backend.set_floatx(float_dtype)).
|